Bibliographic record
Abstract
Roxanne Pinson,1 Bahman Sotoodian,2 Loretta Fiorillo2,3 1School of Medicine, 2Division of Dermatology and Cutaneous Sciences, Department of Medicine, 3Division of Pediatric Dermatology, Department of Pediatrics, University of Alberta, Edmonton, AB, Canada Abstract: The clinical presentation, disease associations, and diverse treatment modalities in overcoming the challenges of managing pediatric psoriasis have been extensively summarized in this article. An extensive literature review revealed the differences in presentation of psoriasis during infancy, childhood, and adolescence. We also summarized the latest topical, systemic, and biological modalities in treating recalcitrant psoriasis. The association of psoriasis with juvenile arthritis and obesity and the significant influence of the disease on the children's quality of life were explored. The clinical presentation of psoriasis can evolve during the child's lifespan. While many treatment modalities already exist for treating pediatric psoriasis, some of the new biologics that are approved for adult patients have not been investigated in the pediatric population and no algorithm exists for their use in this population. Large clinical studies in the future will enhance our understanding with regards to their safety and potential implications in pediatric populations. Keywords: pediatric, epidemiology, juvenile arthritis, topical treatment, systemic treatment, phototherapy, biologics
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".